Abstract
We apply two computational intelligence techniques, namely, Artificial Neural Network and Genetic Algorithm to the growth of self-assembled quantum dots. The method relies on an existing database of growth parameters with a resulting quantum dot characteristic to be able to later obtain the growth parameters needed to reach a specific value for such a quantum dot characteristic. The computational techniques were used to associate the growth input parameters with the mean height of the deposited quantum dots.
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